Search based software engineering: Trends, techniques and applications

© ACM, 2012. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version is available from the link below.In the past five years there has been a dramatic increase in work on Search-Based Software Engineering (SBSE), an approach to Software Engineering (SE) in which Search-Based Optimization (SBO) algorithms are used to address problems in SE. SBSE has been applied to problems throughout the SE lifecycle, from requirements and project planning to maintenance and reengineering. The approach is attractive because it offers a suite of adaptive automated and semiautomated solutions in situations typified by large complex problem spaces with multiple competing and conflicting objectives. This article provides a review and classification of literature on SBSE. The work identifies research trends and relationships between the techniques applied and the applications to which they have been applied and highlights gaps in the literature and avenues for further research.EPSRC and E

A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment

Software quality is an important research area and has gain considerable attention from software engineering community in identification of priority quality attributes in software development process. This thesis describes original research in the field of software quality model by presenting a Feature Ranking Algorithm (FRA) for Pragmatic Quality Factor (PQF) model. The proposed algorithm is able to improve the weaknesses in PQF model in updating and learning the important attributes for software quality assessment. The existing assessment techniques lack of the capability to rank the quality attributes and data learning which can enhance the quality assessment process. The aim of the study is to identify and propose the application of Artificial Intelligence (AI) technique for improving quality assessment technique in PQF model. Therefore, FRA using FRT was constructed and the performance of the FRA was evaluated. The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. The result shows that the performance of FRA correlates strongly to PQF model with 98% correlation compared to the Kolmogorov-Smirnov Correlation Based Filter (KSCBF) algorithm with 83% correlation. Statistical significance test was also performed with score of 0.052 compared to the KSCBF algorithm with score of 0.048. The result shows that the FRA was more significant than KSCBF algorithm. The main contribution of this research is on the implementation of FRT with proposed Most Priority of Features (MPF) calculation in FRA for attributes assessment. Overall, the findings and contributions can be regarded as a novel effort in software quality for attributes selection

A Taxonomy of Workflow Management Systems for Grid Computing

With the advent of Grid and application technologies, scientists and engineers are building more and more complex applications to manage and process large data sets, and execute scientific experiments on distributed resources. Such application scenarios require means for composing and executing complex workflows. Therefore, many efforts have been made towards the development of workflow management systems for Grid computing. In this paper, we propose a taxonomy that characterizes and classifies various approaches for building and executing workflows on Grids. We also survey several representative Grid workflow systems developed by various projects world-wide to demonstrate the comprehensiveness of the taxonomy. The taxonomy not only highlights the design and engineering similarities and differences of state-of-the-art in Grid workflow systems, but also identifies the areas that need further research.Comment: 29 pages, 15 figure

The relationship between search based software engineering and predictive modeling

Search Based Software Engineering (SBSE) is an approach to software engineering in which search based optimization algorithms are used to identify optimal or near optimal solutions and to yield insight. SBSE techniques can cater for multiple, possibly competing objectives and/or constraints and applications where the potential solution space is large and complex. This paper will provide a brief overview of SBSE, explaining some of the ways in which it has already been applied to construction of predictive models. There is a mutually beneficial relationship between predictive models and SBSE. The paper sets out eleven open problem areas for Search Based Predictive Modeling and describes how predictive models also have role to play in improving SBSE

Air Force Institute of Technology Research Report 2007

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

Conceptual model for usable multi-modal mobile assistance during Umrah

Performing Umrah is very demanding and to be performed in very crowded environments. In response to that, many efforts have been initiated to overcome the difficulties faced by pilgrims. However, those efforts focus on acquiring initial perspective and background knowledge before going to Mecca. Findings of preliminary study show that those efforts do not support multi-modality for user interaction. Nowadays the computational capabilities in mobile phones enable it to serve people in various aspects of daily life. Consequently, the mobile phone penetration has increased dramatically in the last decade. Hence, this study aims to propose a comprehensive conceptual model for usable multimodal mobile assistance during Umrah called Multi-model Mobile Assistance during Umrah (MMA-U). Thus, four (4) supporting objectives are formulated, and the Design Science Research Methodology has been adopted. For the usability of MMA-U, Systematic Literature Review (SLR) indicates ten (10) attributes: usefulness, errors rate, simplicity, reliability, ease of use, safety, flexibility, accessibility, attitude, and acceptability. Meanwhile, the content and comparative analysis result in five (5) components that construct the conceptual model of MMA-U: structural, content composition, design principles, development approach, technology, and the design and usability theories. Then, the MMA-U has been reviewed and well-accepted by 15 experts. Later, the MMA-U was incorporated into a prototype called Personal Digital Mutawwif (PDM). The PDM was developed for the purpose of user test in the field. The findings indicate that PDM facilitates the execution of Umrah and successfully meet pilgrims’ needs and expectations. Also, the pilgrims were satisfied and felt that they need to have PDM. In fact, they would recommend PDM to their friends, which mean that use of PDM is safe and suitable while performing Umrah. As a conclusion, the theoretical contribution; the conceptual model of MMA-U; provides guidelines for developing multimodal content mobile applications during Umrah

Electronic reliability prediction: a study over 25 years

This thesis describes research work that the author has undertaken and published in the field of electronic reliability prediction techniques over the last 25 years. Reliability prediction is an important area since it has been part of the backbone of reliability engineering in one form or another for over fifty years. The author has over 45 publications that are within the area of reliability prediction and 13 of these have been selected for review in this thesis. In order to show how the author’s work has contributed to the field of reliability prediction this document also contains information on the history of reliability prediction. This allows the author’s work to be placed in context with general developments in the field. The contributions to knowledge and innovations that have been made in reliability prediction include the development of statistical models for lifetime prediction using early life data (i.e. prognostics); the use of non-constant failure rates for reliability prediction; the use of neural networks for reliability prediction, the use of artificial intelligence systems to support reliability engineers’ decision making; the use of a holistic approach to reliability; the use of complex discrete events simulation to model equipment availability; demonstration of the weaknesses of classical reliability prediction; an understanding of the basic behaviour of no fault founds; the development of a parametric drift model; identification of the use of a reliability database to improve the reliability of systems; and an understanding of the issues that surround the use of new reliability metrics in the aerospace industry